scholarly journals Analysis of Principal Nonlinear Components for the Construction of a Socioeconomic Stratification Index in Ecuador

2021 ◽  
pp. 43-82
Author(s):  
Katherine Morales ◽  
Miguel Flores ◽  
Yasmín Salazar Méndez
Keyword(s):  
Socioeconomic Stratification ◽  
Nonlinear Components

Improvement of Carrier Power to Third-Order Intermodulation Distortion Power Ratio for a Power Amplifier at 5.25 GHz using LINC Method

2018 ◽  
Vol 12 (1) ◽  
pp. 34-40
Author(s):  
Said Elkhaldi ◽  
Naima Amar Touhami ◽  
Mohamed Aghoutane ◽  
Taj-eddin Elhamadi
Keyword(s):  
Power Amplifier ◽  
Artificial Neural Network Model ◽  
Power Ratio ◽  
Linear Amplification ◽  
Third Order ◽  
Gaas Mesfet ◽  
Constant Envelope ◽  
Modulation Signal ◽  
Low Efficiency ◽  
Nonlinear Components

Introduction:This paper focuses on improving the power amplifier linearity for wireless communications. The use of a single branch of a power amplifier can produce high distortion with low efficiency.Method:In this paper, the Linear Amplification with Nonlinear Components (LINC) technique is used to improve the linearity and efficiency of the power amplifier. The LINC technique is based on converting the envelope modulation signal into two constant envelope phase-modulated baseband signals. After amplification and combining the resulting signals, the required linear output signal is obtained. To validate the proposed approach, LINC technique is used for linearizing an amplifier based on a GaAs MESFET (described by an artificial neural network Model).Conclusion:Good results have been achieved, and an improvement of about 40.80 dBc and 47.50 dBc respectively is obtained for the Δlower C/I and Δupper C/I at 5.25 GHz.

Simulation-based site amplification model for shallow bedrock sites in Korea

2021 ◽  
pp. 875529302098198
Author(s):  
Muhammad Aaqib ◽  
Duhee Park ◽  
Muhammad Bilal Adeel ◽  
Youssef M A Hashash ◽  
Okan Ilhan
Keyword(s):  
Linear Models ◽  
Site Response ◽  
Site Amplification ◽  
One Dimensional ◽  
Nonlinear Component ◽  
Nonlinear Site Response ◽  
Simulation Based ◽  
Linear And Nonlinear ◽  
Input Motion ◽  
Nonlinear Components

A new simulation-based site amplification model for shallow sites with thickness less than 30 m in Korea is developed. The site amplification model consists of linear and nonlinear components that are developed from one-dimensional linear and nonlinear site response analyses. A suite of measured shear wave velocity profiles is used to develop corresponding randomized profiles. A VS30 scaled linear amplification model and a model dependent on both VS30 and site period are developed. The proposed linear models compare well with the amplification equations developed for the western United States (WUS) at short periods but show a distinct curved bump between 0.1 and 0.5 s that corresponds to the range of site natural periods of shallow sites. The response at periods longer than 0.5 s is demonstrated to be lower than those of the WUS models. The functional form widely used in both WUS and central and eastern North America (CENA), for the nonlinear component of the site amplification model, is employed in this study. The slope of the proposed nonlinear component with respect to the input motion intensity is demonstrated to be higher than those of both the WUS and CENA models, particularly for soft sites with VS30 < 300 m/s and at periods shorter than 0.2 s. The nonlinear component deviates from the models for generic sites even at low ground motion intensities. The comparisons highlight the uniqueness of the amplification characteristics of shallow sites that a generic site amplification model is unable to capture.

Response dynamics and receptive-field organization of catfish amacrine cells

1992 ◽  
Vol 67 (2) ◽  
pp. 430-442 ◽  
Author(s):  
H. M. Sakai ◽  
K. Naka
Keyword(s):  
Receptive Field ◽  
White Noise ◽  
Amacrine Cells ◽  
Second Order ◽  
Response Dynamics ◽  
Field Center ◽  
Mean Luminance ◽  
Nonlinear Components ◽  
Receptive Field Center ◽  
Dc Potentials

1. We have applied Wiener analysis to a study of response dynamics of N (sustained) and C (transient) amacrine cells. Stimuli were a spot and an annulus of light, the luminance of which was modulated by two independent white-noise signals. First- and second-order Wiener kernels were computed for each spot and annulus input. The analysis allowed us to separate a modulation response into its linear and nonlinear components, and into responses generated by a receptive-field center and its surround. 2. Organization of the receptive field of N amacrine cells consists of both linear and nonlinear components. The receptive field of linear components was center-surround concentric and opposite in polarity, whereas that of second-order nonlinear components was monotonic. 3. In NA (center-depolarizing) amacrine cells, the membrane DC potentials brought about by the mean luminance of a white-noise spot or a steady spot were depolarizations, whereas those brought about by the mean luminance of a white-noise annulus or a steady annulus were hyperpolarizations. In NB (center-hyperpolarizing) amacrine cells, this relationship was reversed. If both receptive-field center and surround were stimulated by a spot and annulus, membrane DC potentials became close to the dark level and the amplitude of modulation responses became larger. 4. The linear responses of a receptive-field center of an N amacrine cell, measured in terms of the first-order Wiener kernel, were facilitated if the surround was stimulated simultaneously. The amplitude of the kernel became larger, and its peak response time became shorter. The same facilitation occurred in the linear responses of a receptive-field surround if the center was stimulated simultaneously. 5. The second-order nonlinear responses were not usually generated in N amacrine cells if the stimulus was either a white-noise spot or a white-noise annulus alone. Significant second-order nonlinearity appeared if the other region of the receptive field was also stimulated. 6. Membrane DC potentials of C amacrine cells remained at the dark level with either a white-noise spot or a white-noise annulus. The cell responded only to modulations. 7. The major characteristics of center and surround responses of C amacrine cells could be approximated by second-order Wiener kernels of the same structure. The receptive field of second-order nonlinear components of C amacrine cells was monotonic.(ABSTRACT TRUNCATED AT 400 WORDS)

Gray-Box Approach for Fault Detection of Dynamical Systems

2003 ◽  
Vol 125 (3) ◽  
pp. 451-454 ◽  
Author(s):  
Han G. Park ◽  
Michail Zak
Keyword(s):  
Neural Network ◽  
Time Delay ◽  
Fault Detection ◽  
Stochastic Model ◽  
Deterministic Model ◽  
Feed Forward Neural Network ◽  
The Neural Network ◽  
Simulated System ◽  
Auto Regressive ◽  
Nonlinear Components

We present a fault detection method called the gray-box. The term “gray-box” refers to the approach wherein a deterministic model of system, i.e., “white box,” is used to filter the data and generate a residual, while a stochastic model, i.e., “black-box” is used to describe the residual. The residual is described by a three-tier stochastic model. An auto-regressive process, and a time-delay feed-forward neural network describe the linear and nonlinear components of the residual, respectively. The last component, the noise, is characterized by its moments. Faults are detected by monitoring the parameters of the auto-regressive model, the weights of the neural network, and the moments of noise. This method is demonstrated on a simulated system of a gas turbine with time delay feedback actuator.

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